Systems, methods and computer-accessible mediums can be provided that can determine an audience interest distribution(s) of content(s) by, for example, receiving first information related to a web behavior(s) of a user(s), determining second information related to a user interest distribution(s) of the user(s) based on the first information, and determining determine the audience interest distribution(s) of the content(s) based on the second information.
Legal claims defining the scope of protection, as filed with the USPTO.
1. A non-transitory computer-accessible medium having stored thereon computer-executable instructions for determining at least one audience interest distribution of at least one first content, wherein, when a computer hardware arrangement executes the instructions, the computer hardware arrangement is configured to perform procedures comprising: a. receiving first information related to at least one score for the at least one first content and at least one second content, wherein the at least one score is based on a plurality of categories assigned to the at least one first content and the at least one second content; b. determining second information related to a total number of times each of a plurality of users interacted with the at least one first content and the at least one second content; c. determining third information related, to an importance level of (i) the at least one first content for each of the plurality of categories based on the first information and (ii) the at least one second content for each of the plurality of categories based on the first information; d. determining fourth information related to an importance level of each of the plurality of categories for (i) the at least one first content based on the first information and (ii) the at least one second content based on the first information; e. determining a plurality of user interest distributions, wherein a user interest distribution for a particular user is based on the second information associated with the particular user, and the fourth information, and wherein the user interest distribution for the particular user includes a set of scores for each of a plurality of further categories; and f. determining the at least one audience interest distribution of the at least one first content using the plurality of user interest distributions based on the second information, the third information and the fourth information, wherein the at least one first content is different from the at least one second content.
2. The non-transitory computer-accessible medium of claim 1 , wherein the computer arrangement is further configured to determine the audience interest distributions based on at least one probabilistic model of the plurality of user interest distributions the second information, the third information and the fourth information.
3. The non-transitory computer-accessible medium of claim 2 , wherein the at least one probabilistic model includes a maximum likelihood estimator.
4. The non-transitory computer-accessible medium of claim 1 , wherein the at least one first content and the at least one second content include at least one webpage.
5. The non-transitory computer-accessible medium of claim 1 , wherein the plurality of categories are based on a type of content that the at least one first content and the at least one second content belong to.
6. The non-transitory computer-accessible medium of claim 1 , wherein the at least one score is based on semantics and natural language processing applied to the at least one first content and the at least one second content.
7. The non-transitory computer-accessible medium of claim 1 , wherein the plurality of categories include a plurality of topical interest categories associated with the at least one first content and the at least one second content.
8. The non-transitory computer-accessible medium of claim 1 , wherein the computer arrangement is further configured to determine the plurality of categories based on at least one further content.
9. The non-transitory computer-accessible medium of claim 1 , wherein the plurality of user interest distributions include further information related to inherent preferences by each of the users for at least one of the plurality of categories.
10. The non-transitory computer-accessible medium of claim 1 , wherein the computer hardware arrangement is configured to determine the at least one audience distribution using a weighted mean of the plurality of user interest distributions, wherein the weighted mean is based on the second information, the third information and the fourth information.
11. The non-transitory computer-accessible medium of claim 1 , wherein the computer arrangement is further configured to model the user interest distributions using at least one matrix based on the second information and the fourth information, and wherein each row vector of the at least one matrix represents at least one user and each column of the at least one matrix represents at least one category.
12. The non-transitory computer-accessible medium of claim 1 , wherein the computer arrangement is further configured to determine the audience interest distributions based on a multinomial distribution model.
13. The non-transitory computer-accessible medium of claim 1 , wherein the computer arrangement is further configured to determine the plurality of user interest distributions by inferring the user interest distributions based on an inference model having a multinomial distribution.
14. The non-transitory computer-accessible medium of claim 13 , wherein the inference model is an estimation of at least one of the plurality of user interest distributions based on a behavior of the users.
15. The non-transitory computer-accessible medium of claim 13 , wherein the computer arrangement is further configured to generate the inference model by probabilistically modeling interactions of the users to a plurality of contents.
16. The non-transitory computer-accessible medium of claim 1 , wherein the computer arrangement is further configured to determine the plurality of user interest distributions using at least one bipartite graph.
17. The non-transitory computer-accessible medium of claim 1 , wherein the at least one first content and the at least one second content include at least one of (i) at least one video game, (ii) at least one movie, (iii) at least one song.
18. A method for determining at least one audience interest distribution of at least one first content, comprising: a. receiving first information related to at least one score for the at least one first content and at least one second content, wherein the at least one score is based on a plurality of categories assigned to the at least one first content and the at least one second content; b. determining second information related to a total number of times each of a plurality of users interacted with the at least one first content and the at least one second content; c. determining third information related to an importance level of (i) the at least one first content for each of the plurality of categories based on the first information and (ii) the at least one second content for each of the plurality of categories based on the first information; d. determining fourth information related to an importance level of each of the plurality of categories for (i) the at least one first content based on the first information and (ii) the at least one second content based on the first information; e. determining a plurality of user interest distributions, wherein a user interest distribution for a particular user is based on the second information associated with the particular user, and the fourth information, and wherein the user interest distribution for the particular user includes a set of scores for each of a plurality of further categories; and f. using a computer hardware arrangement, determining the at least one audience interest distribution of the at least one first content using the plurality of user interest distributions based on the second information, the third information and the fourth information, wherein the at least one first content is different from the at least one second content.
19. A system for determining at least one audience interest distribution of at least one first content, comprising: a computer processing arrangement configured to: a. receive first information related to at least one score for the at least one first content and at least one second content, wherein the at least one score is based on a plurality of categories assigned to the at least one first content and the at least one second content; b. determine second information related to a total number of times each of a plurality of users interacted with the at least one first content and the at least one second content; c. determine third information related to an importance, level of (i) the at least one first content for each of the plurality of categories based on the first information and (ii) the at least one second content for each of the plurality of categories based on the first information; d. determine fourth information related to an importance level of each of the plurality of categories for (i) the at least one first content based on the first information and (ii) the at least one second content based on the first information; e. determine a plurality of user interest distributions, wherein a user interest distribution for a particular user is based on the second information associated with the particular user, and the fourth information, and wherein the user interest distribution for the particular user includes a set of scores for each of a plurality of further categories; and f. determine the at least one audience interest distribution of the at least one first content using the plurality of user interest distributions based on the second information, the third information and the fourth information, wherein the at least one first content is different from the at least one second content.
Cooperative Patent Classification codes for this invention. Click any code to explore related patents in that topic.
September 17, 2013
March 24, 2020
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